發(fā)布時間：2018-06-25 10:03

  本文選題：認(rèn)知無線電 + 頻譜預(yù)測��； 參考：《北京交通大學(xué)》2014年博士論文

【摘要】：頻譜感知、頻譜決策、頻譜共享、頻譜搬移是認(rèn)知無線電技術(shù)的四大功能。次級用戶通過頻譜感知發(fā)掘頻譜空穴,并通過頻譜決策、頻譜共享、頻譜搬移三個功能對發(fā)掘的頻譜空穴加以利用。傳統(tǒng)的頻譜感知、頻譜決策、頻譜共享和頻譜搬移通常造成較大的處理時延、反應(yīng)時延、以及能量消耗。為了解決上述問題,研究人員提出了頻譜預(yù)測技術(shù),利用不同的方法實現(xiàn)對未來時刻的頻譜狀態(tài)的預(yù)測。已有工作尚未針對如何利用次級用戶之間的合作,改善未來時刻頻譜狀態(tài)預(yù)測準(zhǔn)確率這一問題展開研究。此外,如何預(yù)測更多的頻譜參數(shù),并充分利用這些參數(shù)進一步改善認(rèn)知無線電網(wǎng)絡(luò)的整體性能,也是頻譜預(yù)測技術(shù)研究領(lǐng)域有待解決的難點之一。本論文針對上述難點問題,對認(rèn)知無線電網(wǎng)絡(luò)中的頻譜預(yù)測技術(shù)進行深入詳細(xì)的研究。主要內(nèi)容及創(chuàng)新點包括： 1.研究了認(rèn)知無線電網(wǎng)絡(luò)中的協(xié)作頻譜狀態(tài)預(yù)測問題。認(rèn)識到已有的單個次級用戶單獨進行的本地頻譜狀態(tài)預(yù)測方法預(yù)測準(zhǔn)確率有限的問題,充分利用次級用戶之間自發(fā)的合作,提出一種新的協(xié)作頻譜狀態(tài)預(yù)測方法,改善頻譜狀態(tài)預(yù)測的準(zhǔn)確率。具體而言： 1)將次級用戶之間的合作過程建模為一個合作博弈過程,并基于合作博弈理論以最大化次級用戶的頻譜預(yù)測準(zhǔn)確率為目標(biāo)提出了一種新的合作組形成算法。每個合作組內(nèi)選擇一個次級用戶擔(dān)任首領(lǐng),負(fù)責(zé)匯總組內(nèi)其他用戶的本地頻譜狀態(tài)預(yù)測結(jié)果,并通過數(shù)據(jù)融合獲得協(xié)作頻譜狀態(tài)預(yù)測結(jié)果。 2)將設(shè)計的協(xié)作頻譜狀態(tài)預(yù)測方法擴展到任意多個初級用戶任意多個次級用戶構(gòu)成的認(rèn)知無線電網(wǎng)絡(luò)中,改善算法的普適性�；谌蝿�(wù)分配的思想,將次級用戶分類,每一類用戶只對一個初級用戶的授權(quán)頻譜進行協(xié)作頻譜狀態(tài)預(yù)測,有效降低了多個初級用戶場景下協(xié)作頻譜狀態(tài)預(yù)測的復(fù)雜度。 2.研究了基于頻譜狀態(tài)持續(xù)時間預(yù)測的次級用戶頻譜感知間隔優(yōu)化方法。傳統(tǒng)的頻譜感知技術(shù)要求次級用戶在每個時隙的開始階段進行一次頻譜感知。而真實頻譜使用數(shù)據(jù)則表明任一頻譜狀態(tài)都以一定概率持續(xù)若干時隙。在上述背景下,次級用戶的最優(yōu)頻譜感知間隔,即次級用戶兩次頻譜感知之間間隔多少個時隙,成為一個值得研究的課題。具體的研究包括： 1)次級用戶用一個隱馬爾科夫模型來描述頻譜狀態(tài)的變化規(guī)律,并通過分析該模型預(yù)測頻譜狀態(tài)的持續(xù)時間。 2)基于對頻譜狀態(tài)持續(xù)時間的預(yù)測結(jié)果,進一步預(yù)測次級用戶采用某一頻譜感知間隔時將會錯過的傳輸機會、對初級用戶造成的干擾、以及次級用戶網(wǎng)絡(luò)的吞吐量等指標(biāo)。針對每個指標(biāo),基于Sigmoid函數(shù)設(shè)計次級用戶的滿意度函數(shù)。綜合考慮各個指標(biāo)的滿意度,次級用戶能夠確定最優(yōu)的頻譜感知間隔。 3.設(shè)計了基于頻譜質(zhì)量預(yù)測的動態(tài)頻譜接入方案�？紤]到傳統(tǒng)的隨機動態(tài)頻譜接入方案忽略了接入不同質(zhì)量的頻譜會帶來不同的網(wǎng)絡(luò)性能這一問題,提出一種新型的基于頻譜質(zhì)量預(yù)測的動態(tài)頻譜接入方案,使得次級用戶能夠優(yōu)先選擇高質(zhì)量頻譜進行接入,從而有效改善網(wǎng)絡(luò)性能。具體而言： 1)次級用戶用非平穩(wěn)隱馬爾科夫模型準(zhǔn)確的描述頻譜狀態(tài)的變化過程及自身的頻譜感知過程,并通過貝葉斯推斷估計非平穩(wěn)隱馬爾科夫模型的參數(shù)。 2)通過分析貝葉斯推斷獲得的非平穩(wěn)隱馬爾科夫模型參數(shù),次級用戶對頻譜的空閑時間長度、次級用戶在頻譜上進行頻譜感知的檢測概率和誤警概率進行預(yù)測。綜合上述指標(biāo),定義新型的頻譜質(zhì)量評價指標(biāo)從而實現(xiàn)次級用戶對頻譜質(zhì)量的預(yù)測。 3)設(shè)計一種新型的基于頻譜質(zhì)量預(yù)測的動態(tài)頻譜接入方案。方案中,次級用戶依據(jù)頻譜質(zhì)量預(yù)測結(jié)果對所有頻譜進行排序。當(dāng)需要接入頻譜時,次級用戶優(yōu)先選擇質(zhì)量較高的頻譜進行頻譜感知和接入。
[Abstract]:Spectrum sensing, spectrum decision, spectrum sharing, and spectrum moving are the four major functions of cognitive radio. Secondary users discover spectrum holes through spectrum sensing, and use the three functions of spectrum decision, spectrum sharing and spectrum removal to exploit spectrum holes. Traditional spectrum sensing, spectrum decision, spectrum sharing and spectrum removal In order to solve the above problems, researchers have proposed spectrum prediction technology to predict the spectrum state of the future time by using different methods. In addition, how to predict more spectrum parameters and make full use of these parameters to further improve the overall performance of cognitive radio networks is one of the difficulties to be solved in the field of spectrum prediction technology. This paper aims at the above difficulties to predict the spectrum of spectrum in cognitive radio networks. The main contents and innovations include:
1. the problem of cooperative spectrum state prediction in cognitive radio networks is studied. Recognizing the problem that the local spectrum state prediction method of individual secondary users has limited prediction accuracy, we make full use of the spontaneous cooperation between secondary users, and propose a new cooperative spectrum state prediction method to improve the spectrum state precondition. The accuracy of the test.
1) the cooperation process between secondary users is modeled as a cooperative game process, and a new cooperative group formation algorithm is proposed based on the cooperative game theory to maximize the frequency prediction accuracy of the secondary users. In each group, a secondary user is selected as the head leader to collect the local spectrum of other users in the group. The state prediction results are obtained and the result of cooperative spectrum state prediction is obtained through data fusion.
2) the proposed cooperative spectrum state prediction method is extended to the cognitive radio network composed of any multiple primary users, and the universality of the algorithm is improved. Based on the task allocation idea, the secondary users are classified, and each class of users can only predict the cooperative spectrum state of the authorized spectrum of a primary user. The efficiency of cooperative spectrum state prediction in multiple primary user scenarios is reduced.
2. the secondary user spectrum sensing interval optimization method based on the spectrum state duration prediction is studied. The traditional spectrum sensing technology requires secondary users to perform a spectrum sensing at the beginning of each slot. And the real spectrum data shows that any spectrum state continues to a certain number of slots at a certain probability. At the same time, the optimal spectrum sensing interval of secondary users, that is, how many time slots interval between secondary users' two spectrum sensing, has become a subject worthy of study.
1) secondary users use a hidden Markov model to describe the change of spectrum state, and predict the duration of spectrum state by analyzing the model.
2) based on the prediction results of the duration of the spectrum status, we can further predict the transmission opportunities that the secondary users will miss, the interference to the primary users and the throughput of the secondary user network, and design the satisfaction function of the secondary users based on the Sigmoid function. Considering the satisfaction of each index, secondary users can determine the optimal spectrum sensing interval.
3. the dynamic spectrum access scheme based on the spectrum quality prediction is designed. Considering that the traditional random dynamic spectrum access scheme ignores the different network performance with different quality of the spectrum, a new dynamic spectrum access scheme based on the spectrum quality prediction is proposed, so that the secondary users can be selected first. The high quality spectrum is accessed to effectively improve network performance.
1) the secondary user accurately describes the change process of the spectrum state and its spectrum sensing process using the non-stationary hidden Markov model, and estimates the parameters of the nonstationary hidden Markov model by Bayesian inference.
2) by analyzing the parameters of the non-stationary hidden Markov model obtained by Bayesian inference, the secondary user has the free time length of the spectrum, the secondary user predicts the detection probability and the false alarm probability of the spectrum perception on the spectrum, and defines the new spectrum quality evaluation index to realize the secondary user's spectrum quality. Prediction of quantity.
3) a new dynamic spectrum access scheme based on spectrum quality prediction is designed. In the scheme, the secondary user sort all the spectrum according to the spectrum quality prediction results. When the spectrum is needed, the secondary user selects the high quality spectrum for spectrum sensing and joining.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2014
【分類號】：TN925

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本文編號：2065541